Non-local image denoising method based on low rank restoration

A non-local, image technology, applied in the field of image processing, can solve the problem that the denoising effect is not ideal, does not consider the difference of pixel block similarity, stripe distortion and other problems, achieves good consistency, high signal-to-noise ratio, simple and fast algorithm Effect

Inactive Publication Date: 2017-07-07
OCEAN UNIV OF CHINA
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Problems solved by technology

The traditional low-rank representation uses a singular value hard threshold to minimize the nuclear norm, without considerin

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  • Non-local image denoising method based on low rank restoration
  • Non-local image denoising method based on low rank restoration
  • Non-local image denoising method based on low rank restoration

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Embodiment Construction

[0033] Taking image denoising of underwater optical images as an example, the specific implementation process of the present invention will be described in detail in conjunction with the accompanying drawings. The experimental images are collected on the seabed by an automatic underwater vehicle (AUV). The overall process of the present invention is as figure 1 As shown, the specific detailed process is as follows:

[0034] (1) Underwater image acquisition: the underwater image I is collected on the seabed by AUV, and the size of the underwater image is a*b.

[0035] (2) Preprocessing: grayscale transformation is performed on the collected underwater image I, and the grayscale underwater image is denoted as G.

[0036] (3) Noise estimation: Assume that the noise has a mean of 0 and a standard deviation of σ 0 Gaussian white noise.

[0037] (4) Transform domain filtering: perform initial transform domain denoising on the underwater image G, remove most of the noise, and imp...

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Abstract

The invention discloses a non-local image denoising method based on low rank restoration. The method comprises the steps of (1) collecting an image, (2) carrying out gray transformation on the collected image, (3) establishing a three-dimensional similarity matrix through the global search of a similar pixel block for the image which is subjected to gray transformation, then carrying out hard threshold filtering on the discrete cosine transform and Hadamard transform coefficients of the three-dimensional matrix is carried out, obtaining the initial estimation of the similar pixel block with the removal of partial noise, and improving the matching accuracy of the similar pixel block with low rank restoration denoising while removing a large part of noise, and (4) with transform domain filtering as prior knowledge, searching a similar pixel block in a search area for an initially denoised reference pixel block, then forming the similarity matrix by using a similarity block corresponding to an original image, carrying out low rank matrix decomposition on the similarity matrix, effectively separating noise and a signal, and obtaining a final denoised image. The method has the advantages of a simple and fast algorithm, a high signal-to-noise ratio and good consistency and is especially suitable for the requirements of high quality noise reduction of large-scale images.

Description

technical field [0001] The invention relates to a non-local image noise removal method, which belongs to the technical field of image processing. Background technique [0002] Image noise is a ubiquitous phenomenon, which is largely caused by the unavoidable interference of imaging systems, transmission media, and images in the process of acquisition, transmission, and recording, which can easily lead to image quality degradation and hinder image quality. The intuitive image expression, even directly affects the success or failure of key technologies such as feature extraction and target recognition. So it is necessary to denoise the image. On the one hand, it reduces noise while protecting boundaries and details, which has a good effect on subsequent image analysis. [0003] Studies have shown that most of the noise can be represented by Gaussian white noise, impulse noise or a mixture of the two noises. At present, image denoising methods mainly include local methods (m...

Claims

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T5/002G06T2207/20024
Inventor 年睿刘雪飞王志远肖玫
Owner OCEAN UNIV OF CHINA
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